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Webviz config plugins for subsurface data

Project description

PyPI version Build Status Total alerts Language grade: Python Python 3.6 | 3.7 | 3.8 | 3.9 Code style: black

Webviz subsurface

:sparkles::eyeglasses: Live demo application

Introduction

This repository contains subsurface specific standard webviz containers, which are used as plugins in webviz-config.

Installation

The easiest way of installing this package is to run

pip install webviz-subsurface

Add --upgrade if you have installed earlier, but want to upgrade to a newer version.

If you want to install the latest, unreleased, code you can instead run

pip install git+https://github.com/equinor/webviz-subsurface

Usage and documentation

For general usage, see the documentation on webviz-config. End-user documentation for the subsurface containers are automatically built and hosted on the github pages for this repository.

There is also a live demo application showing how a created application can look like, using the master branch of this repository.

Example webviz configuration files

Example webviz configuration files, and corresponding test data, is available at https://github.com/equinor/webviz-subsurface-testdata.

See that repository for instructions on how to download and run the examples.

Creating new elements

If you are interested in creating new elements which can be configured through the configuration file, take a look at the webviz-config contribution guide.

You can do automatic linting of your code changes by running

black --check webviz_subsurface tests # Check code style
pylint webviz_subsurface tests # Check code quality
bandit -r -c ./bandit.yml webviz_subsurface tests  # Check Python security best practice

Review of contributions

When doing review of contributions, it is usually useful to also see the resulting application live, and not only the code changes. In order to facilitate this, this repository is using GitHub actions.

When on a feature branch, and a commit message including the substring [deploy test] arrives, the GitHub action workflow will try to build and deploy a test Docker image for you (which you then can link to a web app with e.g. automatic reload on new images). All you need to do in your own fork is to add GitHub secrets with the following names:

  • review_docker_registry_url: The registry to push to (e.g. myregistry.azurecr.io)
  • review_docker_registry_username: Registry login username.
  • review_docker_registry_token: Registry login token (or password).
  • review_container_name: What you want to call the container pushed to the registry.

You are encouraged to rebase and squash/fixup unnecessary commits before pull request is merged to master.

Disclaimer

This is a tool under heavy development. The current configuration file layout, also for subsurface containers, will therefore see large changes.

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